{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-10T06:54:41.209158Z",
     "start_time": "2019-09-10T06:54:37.293460Z"
    }
   },
   "outputs": [
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       "      <th>ACCEPT_AREA_NAME</th>\n",
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       "      <th>COMPLETE_TIME</th>\n",
       "      <th>CREDIT_BY</th>\n",
       "      <th>REPAY_TIME5</th>\n",
       "      <th>REPAY_TIME6</th>\n",
       "      <th>REPAY_TIME7</th>\n",
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       "      <th>USER_TYPE</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190430151417980420</td>\n",
       "      <td>2019/4/30 7:25:47</td>\n",
       "      <td>WEIXIN</td>\n",
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       "      <th>1</th>\n",
       "      <td>江苏省</td>\n",
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       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
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       "      <th>2</th>\n",
       "      <td>重庆市</td>\n",
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       "      <td>2019/5/1 6:24:16</td>\n",
       "      <td>WEIXIN</td>\n",
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       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190430152512981663</td>\n",
       "      <td>2019/4/30 7:36:48</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>2019/5/8 1:30:16</td>\n",
       "      <td>2019/6/8 1:38:11</td>\n",
       "      <td>2019/7/4 2:37:20</td>\n",
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       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
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       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190430154050983182</td>\n",
       "      <td>2019/4/30 8:14:02</td>\n",
       "      <td>WEIXIN</td>\n",
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       "      <td>2019/5/7 7:41:48</td>\n",
       "      <td>2019/7/8 4:15:13</td>\n",
       "      <td>2019/8/8 1:03:49</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190501122644135175</td>\n",
       "      <td>2019/5/1 4:40:15</td>\n",
       "      <td>ZIZHUSHOUXIN</td>\n",
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       "      <td>2019/7/8 4:16:18</td>\n",
       "      <td>2019/8/3 12:33:22</td>\n",
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       "      <td>201907.0</td>\n",
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       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190505154017385397</td>\n",
       "      <td>2019/5/5 8:37:24</td>\n",
       "      <td>WEIXIN</td>\n",
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       "      <td>2019/7/3 1:03:42</td>\n",
       "      <td>2019/8/3 1:27:35</td>\n",
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       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190516095257807130</td>\n",
       "      <td>2019/5/16 2:04:04</td>\n",
       "      <td>WEIXIN</td>\n",
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       "      <td>2019/7/8 4:15:22</td>\n",
       "      <td>2019/8/3 12:15:25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190509154819544841</td>\n",
       "      <td>2019/5/9 8:38:43</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/8 4:42:35</td>\n",
       "      <td>2019/7/8 4:56:34</td>\n",
       "      <td>2019/8/5 12:15:29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190507131911453180</td>\n",
       "      <td>2019/5/7 5:26:02</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/3 16:41:54</td>\n",
       "      <td>2019/7/3 12:52:57</td>\n",
       "      <td>2019/8/3 11:02:35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190504153740341242</td>\n",
       "      <td>2019/5/4 7:45:42</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/3 17:54:40</td>\n",
       "      <td>2019/7/3 14:12:41</td>\n",
       "      <td>2019/8/8 7:59:35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190506140851417959</td>\n",
       "      <td>2019/5/6 6:21:32</td>\n",
       "      <td>ZIZHUSHOUXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/8 4:55:28</td>\n",
       "      <td>2019/7/8 4:16:20</td>\n",
       "      <td>2019/8/5 14:31:11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190502145022224815</td>\n",
       "      <td>2019/5/2 7:06:01</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/8 4:17:12</td>\n",
       "      <td>2019/7/8 2:45:42</td>\n",
       "      <td>2019/8/8 2:20:02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190504165645348199</td>\n",
       "      <td>2019/5/4 9:43:12</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/5 23:08:12</td>\n",
       "      <td>2019/7/7 12:21:49</td>\n",
       "      <td>2019/8/5 20:41:12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190612144424266125</td>\n",
       "      <td>2019/6/12 7:35:45</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/6 15:11:59</td>\n",
       "      <td>2019/8/5 18:45:23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190601122832704327</td>\n",
       "      <td>2019/6/1 4:49:46</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/3 2:27:55</td>\n",
       "      <td>2019/8/3 2:36:06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190527164421496610</td>\n",
       "      <td>2019/5/27 9:06:05</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/5 20:59:20</td>\n",
       "      <td>2019/7/6 9:24:20</td>\n",
       "      <td>2019/8/5 14:31:19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190526200148467389</td>\n",
       "      <td>2019/5/26 13:43:07</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/8 1:38:58</td>\n",
       "      <td>2019/7/6 14:46:01</td>\n",
       "      <td>2019/8/5 18:22:38</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190630112624133866</td>\n",
       "      <td>2019/6/30 4:03:36</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/8 4:16:13</td>\n",
       "      <td>2019/8/4 10:17:41</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190628171230957714</td>\n",
       "      <td>2019/6/28 9:31:22</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/12 10:01:03</td>\n",
       "      <td>2019/8/4 0:47:40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190624100859758348</td>\n",
       "      <td>2019/6/24 2:18:17</td>\n",
       "      <td>ZIZHUSHOUXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/6 7:48:54</td>\n",
       "      <td>2019/8/5 13:34:19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190423171854681015</td>\n",
       "      <td>2019/4/23 10:18:40</td>\n",
       "      <td>ZIZHUSHOUXIN</td>\n",
       "      <td>2019/5/5 19:56:30</td>\n",
       "      <td>2019/6/5 23:19:28</td>\n",
       "      <td>2019/7/8 4:16:16</td>\n",
       "      <td>2019/8/5 18:40:01</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190424153337711754</td>\n",
       "      <td>2019/4/24 7:41:43</td>\n",
       "      <td>ZIZHUSHOUXIN</td>\n",
       "      <td>2019/5/2 19:22:44</td>\n",
       "      <td>2019/6/2 21:20:18</td>\n",
       "      <td>2019/7/3 1:42:39</td>\n",
       "      <td>2019/8/3 2:09:00</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190424164443716701</td>\n",
       "      <td>2019/4/24 9:42:33</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>2019/5/5 19:57:01</td>\n",
       "      <td>2019/6/5 23:31:54</td>\n",
       "      <td>2019/7/6 12:57:27</td>\n",
       "      <td>2019/8/5 18:54:43</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190424094915691618</td>\n",
       "      <td>2019/4/24 2:03:29</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>2019/5/2 18:01:31</td>\n",
       "      <td>2019/6/2 20:36:01</td>\n",
       "      <td>2019/7/3 0:48:45</td>\n",
       "      <td>2019/8/3 3:01:03</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190423184946685186</td>\n",
       "      <td>2019/4/23 11:19:38</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>2019/5/2 19:01:07</td>\n",
       "      <td>2019/6/2 21:19:32</td>\n",
       "      <td>2019/7/3 1:59:08</td>\n",
       "      <td>2019/8/3 1:37:47</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190423162557677611</td>\n",
       "      <td>2019/4/23 8:47:45</td>\n",
       "      <td>ZIZHUSHOUXIN</td>\n",
       "      <td>2019/5/7 16:54:06</td>\n",
       "      <td>2019/6/6 8:51:35</td>\n",
       "      <td>2019/7/6 16:05:01</td>\n",
       "      <td>2019/8/5 21:47:40</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190404170816828008</td>\n",
       "      <td>2019/4/4 9:27:06</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>2019/4/4 9:45:39</td>\n",
       "      <td>2019/4/4 9:45:39</td>\n",
       "      <td>2019/7/8 4:15:00</td>\n",
       "      <td>2019/8/3 12:54:23</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190403151620782870</td>\n",
       "      <td>2019/4/3 7:25:41</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>2019/5/3 9:09:00</td>\n",
       "      <td>2019/6/3 17:16:02</td>\n",
       "      <td>2019/7/3 12:59:05</td>\n",
       "      <td>2019/8/3 12:27:21</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190402153801749072</td>\n",
       "      <td>2019/4/2 7:52:12</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>2019/5/3 8:42:37</td>\n",
       "      <td>2019/6/3 16:38:29</td>\n",
       "      <td>2019/7/3 12:44:18</td>\n",
       "      <td>2019/8/3 11:02:19</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132858</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190728140112473718</td>\n",
       "      <td>2019/7/28 6:28:06</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/3 17:03:30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132859</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>20190728122939468971</td>\n",
       "      <td>2019/7/28 5:30:50</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 4:58:30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132860</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190720212315132373</td>\n",
       "      <td>2019/7/20 13:41:14</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/3 15:52:18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132861</th>\n",
       "      <td>四川省</td>\n",
       "      <td>20190715153550782038</td>\n",
       "      <td>2019/7/20 3:59:17</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/31 23:34:38</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132862</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190721092013135212</td>\n",
       "      <td>2019/7/21 1:37:17</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/3 20:07:29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132863</th>\n",
       "      <td>四川省</td>\n",
       "      <td>20190721090326134486</td>\n",
       "      <td>2019/7/21 1:24:06</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/21 1:34:28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132864</th>\n",
       "      <td>四川省</td>\n",
       "      <td>20190719184931973538</td>\n",
       "      <td>2019/7/19 11:09:41</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 8:34:33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132865</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190720122051997785</td>\n",
       "      <td>2019/7/20 5:13:59</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/20 5:16:30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132866</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190721094253136440</td>\n",
       "      <td>2019/7/21 2:08:18</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 1:09:02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132867</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190719150921956195</td>\n",
       "      <td>2019/7/19 7:12:25</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/3 18:54:59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132868</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>20190720154235111948</td>\n",
       "      <td>2019/7/20 8:10:02</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 2:52:32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132869</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190720132249102035</td>\n",
       "      <td>2019/7/20 6:07:04</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 1:07:34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132870</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>20190720212952132632</td>\n",
       "      <td>2019/7/20 14:08:17</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/20 14:14:26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132871</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>20190720101541985836</td>\n",
       "      <td>2019/7/20 2:35:21</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/10 2:15:39</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132872</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190719145727955474</td>\n",
       "      <td>2019/7/19 7:21:34</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/2 1:45:22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132873</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>20190720173156121688</td>\n",
       "      <td>2019/7/20 9:51:25</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 8:34:48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132874</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190722101524185496</td>\n",
       "      <td>2019/7/22 2:45:35</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 8:35:30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132875</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>20190722145350201684</td>\n",
       "      <td>2019/7/22 7:25:02</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 2:53:39</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132876</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>20190717144442862969</td>\n",
       "      <td>2019/7/17 6:49:40</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 8:33:51</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132877</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190712101017626047</td>\n",
       "      <td>2019/7/17 8:46:09</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/3 22:37:08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132878</th>\n",
       "      <td>四川省</td>\n",
       "      <td>20190718172326918631</td>\n",
       "      <td>2019/7/18 9:33:19</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 8:10:28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132879</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>20190721083452133741</td>\n",
       "      <td>2019/7/21 1:08:05</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 8:35:11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132880</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190719120952944600</td>\n",
       "      <td>2019/7/19 4:30:40</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 8:34:35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132881</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>20190720141518105420</td>\n",
       "      <td>2019/7/20 6:45:14</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/4 19:06:22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132882</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190701151529195346</td>\n",
       "      <td>2019/7/1 7:47:19</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/3 18:31:57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132883</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>20190701170928202718</td>\n",
       "      <td>2019/7/1 9:23:27</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 2:08:15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132884</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>20190702083245212203</td>\n",
       "      <td>2019/7/2 1:23:14</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/21 23:50:35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132885</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190701134720190515</td>\n",
       "      <td>2019/7/1 5:55:50</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 1:05:36</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132886</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190702101915216383</td>\n",
       "      <td>2019/7/2 2:30:00</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/3 22:12:25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132887</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190702170332240838</td>\n",
       "      <td>2019/7/2 9:10:41</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/3 21:48:56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>132888 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ACCEPT_AREA_NAME            ACCOUNT_ID       COMPLETE_TIME  \\\n",
       "0                   广东省  20190430151417980420   2019/4/30 7:25:47   \n",
       "1                   江苏省  20190501110241123642    2019/5/1 3:08:53   \n",
       "2                   重庆市  20190501135955145327    2019/5/1 6:24:16   \n",
       "3                   重庆市  20190430152512981663   2019/4/30 7:36:48   \n",
       "4                   重庆市  20190430154050983182   2019/4/30 8:14:02   \n",
       "5                   广东省  20190501122644135175    2019/5/1 4:40:15   \n",
       "6                   江苏省  20190505154017385397    2019/5/5 8:37:24   \n",
       "7                   广东省  20190516095257807130   2019/5/16 2:04:04   \n",
       "8                   广东省  20190509154819544841    2019/5/9 8:38:43   \n",
       "9                   江苏省  20190507131911453180    2019/5/7 5:26:02   \n",
       "10                  江苏省  20190504153740341242    2019/5/4 7:45:42   \n",
       "11                  广东省  20190506140851417959    2019/5/6 6:21:32   \n",
       "12                  江苏省  20190502145022224815    2019/5/2 7:06:01   \n",
       "13                  广东省  20190504165645348199    2019/5/4 9:43:12   \n",
       "14                  广东省  20190612144424266125   2019/6/12 7:35:45   \n",
       "15                  江苏省  20190601122832704327    2019/6/1 4:49:46   \n",
       "16                  广东省  20190527164421496610   2019/5/27 9:06:05   \n",
       "17                  广东省  20190526200148467389  2019/5/26 13:43:07   \n",
       "18                  广东省  20190630112624133866   2019/6/30 4:03:36   \n",
       "19                  广东省  20190628171230957714   2019/6/28 9:31:22   \n",
       "20                  广东省  20190624100859758348   2019/6/24 2:18:17   \n",
       "21                  广东省  20190423171854681015  2019/4/23 10:18:40   \n",
       "22                  江苏省  20190424153337711754   2019/4/24 7:41:43   \n",
       "23                  广东省  20190424164443716701   2019/4/24 9:42:33   \n",
       "24                  江苏省  20190424094915691618   2019/4/24 2:03:29   \n",
       "25                  江苏省  20190423184946685186  2019/4/23 11:19:38   \n",
       "26                  广东省  20190423162557677611   2019/4/23 8:47:45   \n",
       "27                  广东省  20190404170816828008    2019/4/4 9:27:06   \n",
       "28                  江苏省  20190403151620782870    2019/4/3 7:25:41   \n",
       "29                  江苏省  20190402153801749072    2019/4/2 7:52:12   \n",
       "...                 ...                   ...                 ...   \n",
       "132858              江苏省  20190728140112473718   2019/7/28 6:28:06   \n",
       "132859         新疆维吾尔自治区  20190728122939468971   2019/7/28 5:30:50   \n",
       "132860              江苏省  20190720212315132373  2019/7/20 13:41:14   \n",
       "132861              四川省  20190715153550782038   2019/7/20 3:59:17   \n",
       "132862              江苏省  20190721092013135212   2019/7/21 1:37:17   \n",
       "132863              四川省  20190721090326134486   2019/7/21 1:24:06   \n",
       "132864              四川省  20190719184931973538  2019/7/19 11:09:41   \n",
       "132865              广东省  20190720122051997785   2019/7/20 5:13:59   \n",
       "132866              重庆市  20190721094253136440   2019/7/21 2:08:18   \n",
       "132867              江苏省  20190719150921956195   2019/7/19 7:12:25   \n",
       "132868              湖北省  20190720154235111948   2019/7/20 8:10:02   \n",
       "132869              重庆市  20190720132249102035   2019/7/20 6:07:04   \n",
       "132870              湖北省  20190720212952132632  2019/7/20 14:08:17   \n",
       "132871              浙江省  20190720101541985836   2019/7/20 2:35:21   \n",
       "132872              重庆市  20190719145727955474   2019/7/19 7:21:34   \n",
       "132873              辽宁省  20190720173156121688   2019/7/20 9:51:25   \n",
       "132874              江苏省  20190722101524185496   2019/7/22 2:45:35   \n",
       "132875              湖北省  20190722145350201684   2019/7/22 7:25:02   \n",
       "132876              浙江省  20190717144442862969   2019/7/17 6:49:40   \n",
       "132877              江苏省  20190712101017626047   2019/7/17 8:46:09   \n",
       "132878              四川省  20190718172326918631   2019/7/18 9:33:19   \n",
       "132879              湖北省  20190721083452133741   2019/7/21 1:08:05   \n",
       "132880              江苏省  20190719120952944600   2019/7/19 4:30:40   \n",
       "132881           内蒙古自治区  20190720141518105420   2019/7/20 6:45:14   \n",
       "132882              江苏省  20190701151529195346    2019/7/1 7:47:19   \n",
       "132883              浙江省  20190701170928202718    2019/7/1 9:23:27   \n",
       "132884              湖北省  20190702083245212203    2019/7/2 1:23:14   \n",
       "132885              广东省  20190701134720190515    2019/7/1 5:55:50   \n",
       "132886              江苏省  20190702101915216383    2019/7/2 2:30:00   \n",
       "132887              江苏省  20190702170332240838    2019/7/2 9:10:41   \n",
       "\n",
       "              CREDIT_BY        REPAY_TIME5        REPAY_TIME6  \\\n",
       "0                WEIXIN   2019/5/8 1:31:29   2019/6/8 1:38:12   \n",
       "1          ZIZHUSHOUXIN                NaN  2019/6/2 19:08:11   \n",
       "2                WEIXIN                NaN   2019/6/8 1:38:04   \n",
       "3                WEIXIN   2019/5/8 1:30:16   2019/6/8 1:38:11   \n",
       "4                WEIXIN   2019/5/7 7:41:48   2019/5/7 7:41:48   \n",
       "5          ZIZHUSHOUXIN                NaN   2019/6/8 4:55:23   \n",
       "6                WEIXIN                NaN  2019/6/9 12:19:48   \n",
       "7                WEIXIN                NaN   2019/6/8 1:38:31   \n",
       "8        MASHANGXIAOJIN                NaN   2019/6/8 4:42:35   \n",
       "9              ZHAOLIAN                NaN  2019/6/3 16:41:54   \n",
       "10       MASHANGXIAOJIN                NaN  2019/6/3 17:54:40   \n",
       "11         ZIZHUSHOUXIN                NaN   2019/6/8 4:55:28   \n",
       "12             ZHAOLIAN                NaN   2019/6/8 4:17:12   \n",
       "13               WEIXIN                NaN  2019/6/5 23:08:12   \n",
       "14               WEIXIN                NaN                NaN   \n",
       "15               WEIXIN                NaN                NaN   \n",
       "16               WEIXIN                NaN  2019/6/5 20:59:20   \n",
       "17               WEIXIN                NaN   2019/6/8 1:38:58   \n",
       "18               WEIXIN                NaN                NaN   \n",
       "19               WEIXIN                NaN                NaN   \n",
       "20         ZIZHUSHOUXIN                NaN                NaN   \n",
       "21         ZIZHUSHOUXIN  2019/5/5 19:56:30  2019/6/5 23:19:28   \n",
       "22         ZIZHUSHOUXIN  2019/5/2 19:22:44  2019/6/2 21:20:18   \n",
       "23               WEIXIN  2019/5/5 19:57:01  2019/6/5 23:31:54   \n",
       "24               WEIXIN  2019/5/2 18:01:31  2019/6/2 20:36:01   \n",
       "25               WEIXIN  2019/5/2 19:01:07  2019/6/2 21:19:32   \n",
       "26         ZIZHUSHOUXIN  2019/5/7 16:54:06   2019/6/6 8:51:35   \n",
       "27               WEIXIN   2019/4/4 9:45:39   2019/4/4 9:45:39   \n",
       "28             ZHAOLIAN   2019/5/3 9:09:00  2019/6/3 17:16:02   \n",
       "29             ZHAOLIAN   2019/5/3 8:42:37  2019/6/3 16:38:29   \n",
       "...                 ...                ...                ...   \n",
       "132858           WEIXIN                NaN                NaN   \n",
       "132859           DUMIAO                NaN                NaN   \n",
       "132860           WEIXIN                NaN                NaN   \n",
       "132861   MASHANGXIAOJIN                NaN                NaN   \n",
       "132862           WEIXIN                NaN                NaN   \n",
       "132863   MASHANGXIAOJIN                NaN                NaN   \n",
       "132864  TIANCHENGRONGZU                NaN                NaN   \n",
       "132865           WEIXIN                NaN                NaN   \n",
       "132866           WEIXIN                NaN                NaN   \n",
       "132867           WEIXIN                NaN                NaN   \n",
       "132868         ZHAOLIAN                NaN                NaN   \n",
       "132869           WEIXIN                NaN                NaN   \n",
       "132870         ZHAOLIAN                NaN                NaN   \n",
       "132871           DUMIAO                NaN                NaN   \n",
       "132872           WEIXIN                NaN                NaN   \n",
       "132873  TIANCHENGRONGZU                NaN                NaN   \n",
       "132874  TIANCHENGRONGZU                NaN                NaN   \n",
       "132875         ZHAOLIAN                NaN                NaN   \n",
       "132876  TIANCHENGRONGZU                NaN                NaN   \n",
       "132877   MASHANGXIAOJIN                NaN                NaN   \n",
       "132878   MASHANGXIAOJIN                NaN                NaN   \n",
       "132879  TIANCHENGRONGZU                NaN                NaN   \n",
       "132880  TIANCHENGRONGZU                NaN                NaN   \n",
       "132881         ZHAOLIAN                NaN                NaN   \n",
       "132882           WEIXIN                NaN                NaN   \n",
       "132883           DUMIAO                NaN                NaN   \n",
       "132884   MASHANGXIAOJIN                NaN                NaN   \n",
       "132885           WEIXIN                NaN                NaN   \n",
       "132886           WEIXIN                NaN                NaN   \n",
       "132887           WEIXIN                NaN                NaN   \n",
       "\n",
       "               REPAY_TIME7         REPAY_TIME8   SEASON5   SEASON6   SEASON7  \\\n",
       "0         2019/7/8 4:15:13   2019/8/3 14:24:01  201905.0  201906.0  201907.0   \n",
       "1         2019/7/3 0:01:03    2019/8/3 0:40:30       NaN  201906.0  201907.0   \n",
       "2        2019/7/15 3:01:25    2019/8/8 1:03:53       NaN  201906.0  201907.0   \n",
       "3         2019/7/4 2:37:20    2019/8/8 1:03:49  201905.0  201906.0  201907.0   \n",
       "4         2019/7/8 4:15:13    2019/8/8 1:03:49  201905.0  201906.0  201907.0   \n",
       "5         2019/7/8 4:16:18   2019/8/3 12:33:22       NaN  201906.0  201907.0   \n",
       "6         2019/7/3 1:03:42    2019/8/3 1:27:35       NaN  201906.0  201907.0   \n",
       "7         2019/7/8 4:15:22   2019/8/3 12:15:25       NaN  201906.0  201907.0   \n",
       "8         2019/7/8 4:56:34   2019/8/5 12:15:29       NaN  201906.0  201907.0   \n",
       "9        2019/7/3 12:52:57   2019/8/3 11:02:35       NaN  201906.0  201907.0   \n",
       "10       2019/7/3 14:12:41    2019/8/8 7:59:35       NaN  201906.0  201907.0   \n",
       "11        2019/7/8 4:16:20   2019/8/5 14:31:11       NaN  201906.0  201907.0   \n",
       "12        2019/7/8 2:45:42    2019/8/8 2:20:02       NaN  201906.0  201907.0   \n",
       "13       2019/7/7 12:21:49   2019/8/5 20:41:12       NaN  201906.0  201907.0   \n",
       "14       2019/7/6 15:11:59   2019/8/5 18:45:23       NaN       NaN  201907.0   \n",
       "15        2019/7/3 2:27:55    2019/8/3 2:36:06       NaN       NaN  201907.0   \n",
       "16        2019/7/6 9:24:20   2019/8/5 14:31:19       NaN  201906.0  201907.0   \n",
       "17       2019/7/6 14:46:01   2019/8/5 18:22:38       NaN  201906.0  201907.0   \n",
       "18        2019/7/8 4:16:13   2019/8/4 10:17:41       NaN       NaN  201907.0   \n",
       "19      2019/7/12 10:01:03    2019/8/4 0:47:40       NaN       NaN  201907.0   \n",
       "20        2019/7/6 7:48:54   2019/8/5 13:34:19       NaN       NaN  201907.0   \n",
       "21        2019/7/8 4:16:16   2019/8/5 18:40:01  201905.0  201906.0  201907.0   \n",
       "22        2019/7/3 1:42:39    2019/8/3 2:09:00  201905.0  201906.0  201907.0   \n",
       "23       2019/7/6 12:57:27   2019/8/5 18:54:43  201905.0  201906.0  201907.0   \n",
       "24        2019/7/3 0:48:45    2019/8/3 3:01:03  201905.0  201906.0  201907.0   \n",
       "25        2019/7/3 1:59:08    2019/8/3 1:37:47  201905.0  201906.0  201907.0   \n",
       "26       2019/7/6 16:05:01   2019/8/5 21:47:40  201905.0  201906.0  201907.0   \n",
       "27        2019/7/8 4:15:00   2019/8/3 12:54:23  201905.0  201906.0  201907.0   \n",
       "28       2019/7/3 12:59:05   2019/8/3 12:27:21  201905.0  201906.0  201907.0   \n",
       "29       2019/7/3 12:44:18   2019/8/3 11:02:19  201905.0  201906.0  201907.0   \n",
       "...                    ...                 ...       ...       ...       ...   \n",
       "132858                 NaN   2019/8/3 17:03:30       NaN       NaN       NaN   \n",
       "132859                 NaN    2019/8/8 4:58:30       NaN       NaN       NaN   \n",
       "132860                 NaN   2019/8/3 15:52:18       NaN       NaN       NaN   \n",
       "132861                 NaN  2019/7/31 23:34:38       NaN       NaN       NaN   \n",
       "132862                 NaN   2019/8/3 20:07:29       NaN       NaN       NaN   \n",
       "132863                 NaN   2019/7/21 1:34:28       NaN       NaN       NaN   \n",
       "132864                 NaN    2019/8/8 8:34:33       NaN       NaN       NaN   \n",
       "132865                 NaN   2019/7/20 5:16:30       NaN       NaN       NaN   \n",
       "132866                 NaN    2019/8/8 1:09:02       NaN       NaN       NaN   \n",
       "132867                 NaN   2019/8/3 18:54:59       NaN       NaN       NaN   \n",
       "132868                 NaN    2019/8/8 2:52:32       NaN       NaN       NaN   \n",
       "132869                 NaN    2019/8/8 1:07:34       NaN       NaN       NaN   \n",
       "132870                 NaN  2019/7/20 14:14:26       NaN       NaN       NaN   \n",
       "132871                 NaN   2019/8/10 2:15:39       NaN       NaN       NaN   \n",
       "132872                 NaN    2019/8/2 1:45:22       NaN       NaN       NaN   \n",
       "132873                 NaN    2019/8/8 8:34:48       NaN       NaN       NaN   \n",
       "132874                 NaN    2019/8/8 8:35:30       NaN       NaN       NaN   \n",
       "132875                 NaN    2019/8/8 2:53:39       NaN       NaN       NaN   \n",
       "132876                 NaN    2019/8/8 8:33:51       NaN       NaN       NaN   \n",
       "132877                 NaN   2019/8/3 22:37:08       NaN       NaN       NaN   \n",
       "132878                 NaN    2019/8/8 8:10:28       NaN       NaN       NaN   \n",
       "132879                 NaN    2019/8/8 8:35:11       NaN       NaN       NaN   \n",
       "132880                 NaN    2019/8/8 8:34:35       NaN       NaN       NaN   \n",
       "132881                 NaN   2019/8/4 19:06:22       NaN       NaN       NaN   \n",
       "132882                 NaN   2019/8/3 18:31:57       NaN       NaN       NaN   \n",
       "132883                 NaN    2019/8/8 2:08:15       NaN       NaN       NaN   \n",
       "132884                 NaN  2019/8/21 23:50:35       NaN       NaN       NaN   \n",
       "132885                 NaN    2019/8/8 1:05:36       NaN       NaN       NaN   \n",
       "132886                 NaN   2019/8/3 22:12:25       NaN       NaN       NaN   \n",
       "132887                 NaN   2019/8/3 21:48:56       NaN       NaN       NaN   \n",
       "\n",
       "        SEASON8 STATUS5 STATUS6 STATUS7 STATUS8  USER_TYPE  \n",
       "0        201908   CLEAR   CLEAR   CLEAR   CLEAR          2  \n",
       "1        201908     NaN   CLEAR   CLEAR   CLEAR          1  \n",
       "2        201908     NaN   CLEAR   CLEAR   CLEAR          2  \n",
       "3        201908   CLEAR   CLEAR   CLEAR   CLEAR          2  \n",
       "4        201908   CLEAR   CLEAR   CLEAR   CLEAR          2  \n",
       "5        201908     NaN   CLEAR   CLEAR   CLEAR          1  \n",
       "6        201908     NaN   CLEAR   CLEAR   CLEAR          2  \n",
       "7        201908     NaN   CLEAR   CLEAR   CLEAR          2  \n",
       "8        201908     NaN   CLEAR   CLEAR   CLEAR          2  \n",
       "9        201908     NaN   CLEAR   CLEAR   CLEAR          2  \n",
       "10       201908     NaN   CLEAR   CLEAR   CLEAR          2  \n",
       "11       201908     NaN   CLEAR   CLEAR   CLEAR          1  \n",
       "12       201908     NaN   CLEAR   CLEAR   CLEAR          2  \n",
       "13       201908     NaN   CLEAR   CLEAR   CLEAR          2  \n",
       "14       201908     NaN     NaN   CLEAR   CLEAR          2  \n",
       "15       201908     NaN     NaN   CLEAR   CLEAR          2  \n",
       "16       201908     NaN   CLEAR   CLEAR   CLEAR          2  \n",
       "17       201908     NaN   CLEAR   CLEAR   CLEAR          2  \n",
       "18       201908     NaN     NaN   CLEAR   CLEAR          2  \n",
       "19       201908     NaN     NaN   CLEAR   CLEAR          2  \n",
       "20       201908     NaN     NaN   CLEAR   CLEAR          1  \n",
       "21       201908   CLEAR   CLEAR   CLEAR   CLEAR          1  \n",
       "22       201908   CLEAR   CLEAR   CLEAR   CLEAR          1  \n",
       "23       201908   CLEAR   CLEAR   CLEAR   CLEAR          2  \n",
       "24       201908   CLEAR   CLEAR   CLEAR   CLEAR          2  \n",
       "25       201908   CLEAR   CLEAR   CLEAR   CLEAR          2  \n",
       "26       201908   CLEAR   CLEAR   CLEAR   CLEAR          1  \n",
       "27       201908   CLEAR   CLEAR   CLEAR   CLEAR          2  \n",
       "28       201908   CLEAR   CLEAR   CLEAR   CLEAR          2  \n",
       "29       201908   CLEAR   CLEAR   CLEAR   CLEAR          2  \n",
       "...         ...     ...     ...     ...     ...        ...  \n",
       "132858   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132859   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132860   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132861   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132862   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132863   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132864   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132865   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132866   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132867   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132868   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132869   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132870   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132871   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132872   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132873   201908     NaN     NaN     NaN   CLEAR          1  \n",
       "132874   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132875   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132876   201908     NaN     NaN     NaN   CLEAR          1  \n",
       "132877   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132878   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132879   201908     NaN     NaN     NaN   CLEAR          1  \n",
       "132880   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132881   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132882   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132883   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132884   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132885   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132886   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "132887   201908     NaN     NaN     NaN   CLEAR          2  \n",
       "\n",
       "[132888 rows x 17 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "\n",
    "# 指定工作目录路径\n",
    "os.chdir('D:\\迁移率')\n",
    "data = pd.read_csv('qianyilv0903.csv',low_memory=False)\n",
    "data1 = data.drop(columns='记录数')\n",
    "data=data1.copy()\n",
    "name = list(data)\n",
    "# 把列名转为大写\n",
    "for n in name:\n",
    "#     print(n.upper())\n",
    "    data.rename(columns={n:n.upper()},inplace=True)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-10T09:15:05.110465Z",
     "start_time": "2019-09-10T09:12:14.200936Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "迁移率数据写入完成！文件位置:D:\\迁移率\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "grant=['ZHONGAN','ZHAOLIAN','MASHANGXIAOJIN','WEIXIN','ZIZHUSHOUXIN','BESTPAY','GUOFU',\n",
    "       'DUMIAO','FENQICHAOREN','ZIYING','TIANCHENGRONGZU']\n",
    "user =[1,2,3,4,5,10]\n",
    "area =[\"广东省\",\"江苏省\",\"重庆市\",\"四川省\",\"新疆维吾尔自治区\",\"浙江省\",\"内蒙古自治区\",\"湖北省\",\"辽宁省\"]\n",
    "\n",
    "# 计算逾期期数\n",
    "# x:series y:账期数\n",
    "def overdue_num(x,y):\n",
    "    o_num = 0\n",
    "    for i in range(5,y+1):\n",
    "        o_num = o_num + int(x['STATUS'+str(i)]=='OPEN') + int(x['REPAY_TIME'+str(i)]>=pd.to_datetime('2019-'+str(y+1)+'-1'))\n",
    "    return o_num\n",
    "\n",
    "for i in grant:\n",
    "    for j in user:\n",
    "        for k in area:\n",
    "            all = data.loc[(data['CREDIT_BY']==i)&(data['USER_TYPE']==j)&(data['ACCEPT_AREA_NAME']==k)].copy()\n",
    "            if all.shape[0] == 0:\n",
    "                pass\n",
    "            else:\n",
    "#                 print(all.shape)\n",
    "\n",
    "\n",
    "                # 转换时间\n",
    "                # all['REPAY_TIME4']=pd.to_datetime(all.REPAY_TIME4,format='%Y-%m-%d')\n",
    "                all['REPAY_TIME5']=pd.to_datetime(all.REPAY_TIME5,format='%Y-%m-%d')\n",
    "                all['REPAY_TIME6']=pd.to_datetime(all.REPAY_TIME6,format='%Y-%m-%d')\n",
    "                all['REPAY_TIME7']=pd.to_datetime(all.REPAY_TIME7,format='%Y-%m-%d')\n",
    "                all['REPAY_TIME8']=pd.to_datetime(all.REPAY_TIME8,format='%Y-%m-%d')\n",
    "                all['COMPLETE_TIME']=pd.to_datetime(all.COMPLETE_TIME,format='%Y-%m-%d').dt.month\n",
    "                # 按完成时间分类\n",
    "                m4 = all[all['COMPLETE_TIME']==4]\n",
    "                m5 = all[all['COMPLETE_TIME']==5]\n",
    "                m6 = all[all['COMPLETE_TIME']==6]\n",
    "                m7 = all[all['COMPLETE_TIME']==7]\n",
    "                m8 = all[all['COMPLETE_TIME']==8]\n",
    "                #4月\n",
    "                #按mob分类\n",
    "                # 4月完成\n",
    "                list_all_c_4 = list(m4['ACCOUNT_ID'])\n",
    "                #5月\n",
    "                #按mob分类\n",
    "                # 4月完成\n",
    "                list_m4_t_5 = list(m4[m4['STATUS5']=='TERMINATE']['ACCOUNT_ID']) + list(m4[m4['STATUS5']=='CLOSE']['ACCOUNT_ID'])\n",
    "                list_m4_m1_5 = list(m4[m4['STATUS5']=='OPEN']['ACCOUNT_ID']) + list(m4[m4['REPAY_TIME5']>='2019-6-1']['ACCOUNT_ID'])\n",
    "                list_m4_c_5  = list(set(m4['ACCOUNT_ID']) ^ set(list_m4_t_5 + list_m4_m1_5))\n",
    "\n",
    "                #总的\n",
    "                list_all_t_5  = list_m4_t_5\n",
    "                list_all_m1_5 = list_m4_m1_5\n",
    "\n",
    "                list_all_c_5  = list_m4_c_5 + list(m5['ACCOUNT_ID'])\n",
    "\n",
    "                #6月            \n",
    "                # 取4月和五月完成的数据\n",
    "                m4_5 = pd.concat([m4,m5],ignore_index=True)\n",
    "                if m4_5.shape[0] > 0:\n",
    "                    # 判断逾期几期并记录到dataframe\n",
    "                    m4_5['overdue_num'] = m4_5.apply(lambda x: overdue_num(x=x,y=6),axis=1)\n",
    "                else:\n",
    "                    m4_5['overdue_num'] = 0\n",
    "                list_all_m1_6 = list(m4_5[m4_5['overdue_num']==1]['ACCOUNT_ID'])\n",
    "                list_all_m2_6 = list(m4_5[m4_5['overdue_num']==2]['ACCOUNT_ID'])\n",
    "                list_all_c_6  = list(m4_5.loc[(m4_5['STATUS6']=='CLEAR') & (m4_5['REPAY_TIME6']<'2019-7-1')]['ACCOUNT_ID']) + list(m6['ACCOUNT_ID']) \n",
    "                \n",
    "\n",
    "                #7月\n",
    "                # 取4-6月完成的数据\n",
    "                m4_6 = pd.concat([m4, m5, m6], ignore_index=True)\n",
    "                if m4_6.shape[0] > 0:\n",
    "                    # 判断逾期几期并记录到dataframe\n",
    "                    m4_6['overdue_num'] = m4_6.apply(lambda x: overdue_num(x=x,y=7), axis=1)\n",
    "                else:\n",
    "                    m4_6['overdue_num'] = 0\n",
    "                list_all_m1_7 = list(m4_6[m4_6['overdue_num'] == 1]['ACCOUNT_ID'])\n",
    "                list_all_m2_7 = list(m4_6[m4_6['overdue_num'] == 2]['ACCOUNT_ID'])\n",
    "                list_all_m3_7 = list(m4_6[m4_6['overdue_num'] == 3]['ACCOUNT_ID'])\n",
    "                list_all_c_7 = list(m4_6.loc[(m4_6['STATUS7'] == 'CLEAR') & (m4_6['REPAY_TIME7'] < '2019-8-1')]['ACCOUNT_ID']) + list(m7['ACCOUNT_ID'])\n",
    "\n",
    "\n",
    "                #8月\n",
    "                # 取4-6月完成的数据\n",
    "                m4_7 = pd.concat([m4, m5, m6, m7], ignore_index=True)\n",
    "                if m4_7.shape[0] > 0:\n",
    "                    # 判断逾期几期并记录到dataframe\n",
    "                    m4_7['overdue_num'] = m4_7.apply(lambda x: overdue_num(x=x,y=8), axis=1)\n",
    "                else:\n",
    "                    m4_7['overdue_num'] = 0\n",
    "                list_all_m1_8 = list(m4_7[m4_7['overdue_num'] == 1]['ACCOUNT_ID'])\n",
    "                list_all_m2_8 = list(m4_7[m4_7['overdue_num'] == 2]['ACCOUNT_ID'])\n",
    "                list_all_m3_8 = list(m4_7[m4_7['overdue_num'] == 3]['ACCOUNT_ID'])\n",
    "                list_all_m4_8 = list(m4_7[m4_7['overdue_num'] == 4]['ACCOUNT_ID'])\n",
    "                list_all_c_8 = list(m4_7.loc[(m4_7['STATUS8'] == 'CLEAR') & (m4_7['REPAY_TIME8'] < '2019-9-1')]['ACCOUNT_ID']) + list(m8['ACCOUNT_ID'])\n",
    "\n",
    "\n",
    "                # 计算结果保存\n",
    "                # C-M1\n",
    "                c_m1_05_z = len(set(list_all_m1_5)&set(list_all_c_4))\n",
    "                c_m1_05_m = len(list_all_c_4)\n",
    "                c_m1_06_z = len(set(list_all_m1_6)&set(list_all_c_5))\n",
    "                c_m1_06_m = len(list_all_c_5)\n",
    "                c_m1_07_z = len(set(list_all_m1_7)&set(list_all_c_6))\n",
    "                c_m1_07_m = len(list_all_c_6)\n",
    "                c_m1_08_z = len(set(list_all_m1_8)&set(list_all_c_7))\n",
    "                c_m1_08_m = len(list_all_c_7)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "                # M1-M2\n",
    "                m1_m2_06_z = len(set(list_all_m2_6)&set(list_all_m1_5))\n",
    "                m1_m2_06_m = len(list_all_m1_5)\n",
    "                m1_m2_07_z = len(set(list_all_m2_7)&set(list_all_m1_6))\n",
    "                m1_m2_07_m = len(list_all_m1_6)\n",
    "                m1_m2_08_z = len(set(list_all_m2_8) & set(list_all_m1_7))\n",
    "                m1_m2_08_m = len(list_all_m1_7)\n",
    "\n",
    "                # M2-M3\n",
    "                m2_m3_07_z = len(set(list_all_m3_7)&set(list_all_m2_6))\n",
    "                m2_m3_07_m = len(list_all_m2_6)\n",
    "                m2_m3_08_z = len(set(list_all_m3_8)&set(list_all_m2_7))\n",
    "                m2_m3_08_m = len(list_all_m2_7)\n",
    "\n",
    "\n",
    "                # M3-M4\n",
    "                m3_m4_08_z = len(list_all_m4_8)\n",
    "                m3_m4_08_m = len(list_all_m3_7)\n",
    "\n",
    "\n",
    "                # C-M2\n",
    "                c_m2_06_z = c_m1_05_z * m1_m2_06_z\n",
    "                c_m2_06_m = c_m1_05_m * m1_m2_06_m\n",
    "                c_m2_07_z = c_m1_06_z * m1_m2_07_z\n",
    "                c_m2_07_m = c_m1_06_m * m1_m2_07_m\n",
    "                c_m2_08_z = c_m1_07_z * m1_m2_08_z\n",
    "                c_m2_08_m = c_m1_07_m * m1_m2_08_m\n",
    "\n",
    "\n",
    "\n",
    "                # C-M3\n",
    "                c_m3_07_z = c_m1_05_z * m1_m2_06_z * m2_m3_07_z\n",
    "                c_m3_07_m = c_m1_05_m * m1_m2_06_m * m2_m3_07_m\n",
    "                c_m3_08_z = c_m1_06_z * m1_m2_07_z * m2_m3_08_z\n",
    "                c_m3_08_m = c_m1_06_m * m1_m2_07_m * m2_m3_08_m\n",
    "\n",
    "\n",
    "                # C-M4\n",
    "                c_m4_08_z = c_m1_05_z * m1_m2_06_z * m2_m3_07_z * m3_m4_08_z\n",
    "                c_m4_08_m = c_m1_05_m * m1_m2_06_m * m2_m3_07_m * m3_m4_08_m\n",
    "\n",
    "\n",
    "                #C-C\n",
    "                c_c_05_z = len(set(list_all_c_4)&set(list_all_c_5))\n",
    "                c_c_05_m = len(set(list_all_c_4))\n",
    "                c_c_06_z = len(set(list_all_c_6)&set(list_all_c_5))\n",
    "                c_c_06_m = len(set(list_all_c_5))\n",
    "                c_c_07_z = len(set(list_all_c_7)&set(list_all_c_6))\n",
    "                c_c_07_m = len(set(list_all_c_6))\n",
    "                c_c_08_z = len(set(list_all_c_8)&set(list_all_c_7))\n",
    "                c_c_08_m = len(set(list_all_c_7))\n",
    "\n",
    "                #M1-C\n",
    "                m1_c_06_z = len(set(list_all_m1_5)&set(list_all_c_6))\n",
    "                m1_c_06_m = len(set(list_all_m1_5))\n",
    "                m1_c_07_z = len(set(list_all_m1_6)&set(list_all_c_7))\n",
    "                m1_c_07_m = len(set(list_all_m1_6))\n",
    "                m1_c_08_z = len(set(list_all_m1_7)&set(list_all_c_8))\n",
    "                m1_c_08_m = len(set(list_all_m1_7))\n",
    "\n",
    "                #M2-C\n",
    "            \n",
    "                m2_c_07_z = len(set(list_all_m2_6)&set(list_all_c_7))\n",
    "                m2_c_07_m = len(list_all_m2_6)\n",
    "                m2_c_08_z = len(set(list_all_m2_7)&set(list_all_c_8))\n",
    "                m2_c_08_m = len(list_all_m2_7)\n",
    "\n",
    "                # M3-C\n",
    "                m3_c_08_z = len(set(list_all_m3_7)&set(list_all_c_8))\n",
    "                m3_c_08_m = len(list_all_m3_7)\n",
    "                #M1-M1\n",
    "\n",
    "                m1_m1_06_z = len(set(list_all_m1_6)&set(list_all_m1_5))\n",
    "                m1_m1_06_m = len(set(list_all_m1_5))\n",
    "                m1_m1_07_z = len(set(list_all_m1_7)&set(list_all_m1_6))\n",
    "                m1_m1_07_m = len(set(list_all_m1_6))\n",
    "                m1_m1_08_z = len(set(list_all_m1_8)&set(list_all_m1_7))\n",
    "                m1_m1_08_m = len(set(list_all_m1_7))\n",
    "\n",
    "\n",
    "                #M2-M1\n",
    "\n",
    "                m2_m1_07_z = len(set(list_all_m2_6)&set(list_all_m1_7))\n",
    "                m2_m1_07_m = len(set(list_all_m2_6))\n",
    "                m2_m1_08_z = len(set(list_all_m2_7)&set(list_all_m1_8))\n",
    "                m2_m1_08_m = len(set(list_all_m2_7))\n",
    "\n",
    "                # M3-M1\n",
    "                m3_m1_08_z = len(set(list_all_m3_7)&set(list_all_m1_8))\n",
    "                m3_m1_08_m = len(list_all_m3_7)\n",
    "\n",
    "                # 数据写入到文件\n",
    "                with open('迁移率(月底)导出.txt', 'a+') as f:\n",
    "                    # C-M1\n",
    "                    c_m1_5 = \"{},{},{},C-M1,201905,{},{}\".format(i,j,k,c_m1_05_z,c_m1_05_m)\n",
    "                    c_m1_6 = \"{},{},{},C-M1,201906,{},{}\".format(i,j,k,c_m1_06_z,c_m1_06_m)\n",
    "                    c_m1_7 = \"{},{},{},C-M1,201907,{},{}\".format(i,j,k,c_m1_07_z,c_m1_07_m)\n",
    "                    c_m1_8 = \"{},{},{},C-M1,201908,{},{}\".format(i,j,k,c_m1_08_z,c_m1_08_m)\n",
    "                    f.write(c_m1_5+'\\n'+c_m1_6+'\\n'+c_m1_7+'\\n'+c_m1_8+'\\n')\n",
    "\n",
    "                    # M1-M2\n",
    "                    m1_m2_6 = \"{},{},{},M1-M2,201906,{},{}\".format(i,j,k,m1_m2_06_z,m1_m2_06_m)\n",
    "                    m1_m2_7 = \"{},{},{},M1-M2,201907,{},{}\".format(i,j,k,m1_m2_07_z,m1_m2_07_m)\n",
    "                    m1_m2_8 = \"{},{},{},M1-M2,201908,{},{}\".format(i,j,k,m1_m2_08_z,m1_m2_08_m)\n",
    "\n",
    "                    f.write(m1_m2_6+'\\n'+m1_m2_7+'\\n'+m1_m2_8+'\\n')\n",
    "\n",
    "                    # M2-M3\n",
    "                    m2_m3_7 = \"{},{},{},M2-M3,201907,{},{}\".format(i,j,k,m2_m3_07_z,m2_m3_07_m)\n",
    "                    m2_m3_8 = \"{},{},{},M2-M3,201908,{},{}\".format(i,j,k,m2_m3_08_z,m2_m3_08_m)\n",
    "\n",
    "                    f.write(m2_m3_7+'\\n' + m2_m3_8+'\\n')\n",
    "\n",
    "                    # M3-M4\n",
    "                    m3_m4_8 = \"{},{},{},M3-M4,201908,{},{}\".format(i,j,k,m3_m4_08_z,m3_m4_08_m)\n",
    "\n",
    "                    f.write(m3_m4_8+'\\n')\n",
    "\n",
    "                    # C-M2\n",
    "                    c_m2_6 = \"{},{},{},C-M2,201906,{},{}\".format(i,j,k,c_m2_06_z,c_m2_06_m)\n",
    "                    c_m2_7 = \"{},{},{},C-M2,201907,{},{}\".format(i,j,k,c_m2_07_z,c_m2_07_m)\n",
    "                    c_m2_8 = \"{},{},{},C-M2,201908,{},{}\".format(i,j,k,c_m2_08_z,c_m2_08_m)\n",
    "\n",
    "                    f.write(c_m2_6+'\\n'+c_m2_7+'\\n'+c_m2_8+'\\n')\n",
    "\n",
    "                    # C-M3\n",
    "                    c_m3_7 = \"{},{},{},C-M3,201907,{},{}\".format(i,j,k,c_m3_07_z,c_m3_07_m)\n",
    "                    c_m3_8 = \"{},{},{},C-M3,201908,{},{}\".format(i,j,k,c_m3_08_z,c_m3_08_m)\n",
    "\n",
    "                    f.write(c_m3_7+'\\n' + c_m3_8+'\\n')\n",
    "\n",
    "                    # C-M4\n",
    "                    c_m4_8 = \"{},{},{},C-M4,201908,{},{}\".format(i,j,k,c_m4_08_z,c_m4_08_m)\n",
    "\n",
    "                    f.write(c_m4_8+'\\n')\n",
    "\n",
    "                    # C-C\n",
    "                    c_c_5 = \"{},{},{},C-C,201905,{},{}\".format(i,j,k,c_c_05_z,c_c_05_m)\n",
    "                    c_c_6 = \"{},{},{},C-C,201906,{},{}\".format(i,j,k,c_c_06_z,c_c_06_m)\n",
    "                    c_c_7 = \"{},{},{},C-C,201907,{},{}\".format(i,j,k,c_c_07_z,c_c_07_m)\n",
    "                    c_c_8 = \"{},{},{},C-C,201908,{},{}\".format(i,j,k,c_c_08_z,c_c_08_m)\n",
    "                    f.write(c_c_5+'\\n'+c_c_6+'\\n'+c_c_7+'\\n'+c_c_8+'\\n')\n",
    "\n",
    "                    # M1-C\n",
    "                    m1_c_6 = \"{},{},{},M1-C,201906,{},{}\".format(i,j,k,m1_c_06_z,m1_c_06_m)\n",
    "                    m1_c_7 = \"{},{},{},M1-C,201907,{},{}\".format(i,j,k,m1_c_07_z,m1_c_07_m)\n",
    "                    m1_c_8 = \"{},{},{},M1-C,201908,{},{}\".format(i,j,k,m1_c_08_z,m1_c_08_m)\n",
    "\n",
    "                    f.write(m1_c_6+'\\n'+m1_c_7+'\\n'+m1_c_8+'\\n')\n",
    "\n",
    "                    # M2-C\n",
    "                    m2_c_7 = \"{},{},{},M2-C,201907,{},{}\".format(i,j,k,m2_c_07_z,m2_c_07_m)\n",
    "                    m2_c_8 = \"{},{},{},M2-C,201908,{},{}\".format(i,j,k,m2_c_08_z,m2_c_08_m)\n",
    "\n",
    "                    f.write(m2_c_7+'\\n' + m2_c_8+'\\n')\n",
    "\n",
    "                    # M3-C\n",
    "                    m3_c_8 = \"{},{},{},M3-C,201908,{},{}\".format(i,j,k,m3_c_08_z,m3_c_08_m)\n",
    "\n",
    "                    f.write(m3_c_8+'\\n')\n",
    "\n",
    "                    # M1-M1\n",
    "                    m1_m1_6 = \"{},{},{},M1-M1,201906,{},{}\".format(i,j,k,m1_m1_06_z,m1_m1_06_m)\n",
    "                    m1_m1_7 = \"{},{},{},M1-M1,201907,{},{}\".format(i,j,k,m1_m1_07_z,m1_m1_07_m)\n",
    "                    m1_m1_8 = \"{},{},{},M1-M1,201908,{},{}\".format(i,j,k,m1_m1_08_z,m1_m1_08_m)\n",
    "\n",
    "                    f.write(m1_m1_6+'\\n'+m1_m1_7+'\\n'+m1_m1_8+'\\n')\n",
    "\n",
    "                    # M2-M1\n",
    "                    m2_m1_7 = \"{},{},{},M2-M1,201907,{},{}\".format(i,j,k,m2_m1_07_z,m2_m1_07_m)\n",
    "                    m2_m1_8 = \"{},{},{},M2-M1,201908,{},{}\".format(i,j,k,m2_m1_08_z,m2_m1_08_m)\n",
    "\n",
    "                    f.write(m2_m1_7+'\\n' + m2_m1_8+'\\n')\n",
    "\n",
    "                    # M3-M1\n",
    "                    m3_m1_8 = \"{},{},{},M3-M1,201908,{},{}\".format(i,j,k,m3_m1_08_z,m3_m1_08_m)\n",
    "\n",
    "                    f.write(m3_m1_8+'\\n')\n",
    "print('迁移率数据写入完成！文件位置:{}'.format(os.getcwd()))\n"
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